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"A tool or platform to search within a codebase" matching MCP servers:

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    Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.
    4
  • A
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    AST-aware codebase indexing with semantic search, exposed as an MCP server. Enables semantic search and file context retrieval across your codebase using natural language queries.
    4
    1
    MIT
  • F
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    Enables dynamic tool discovery and loading for Claude using BM25, regex, and semantic search algorithms. It supports managing a catalog of over 10,000 tools with minimal context overhead and provides a REST API for tool management.
  • F
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    A semantic codebase indexer MCP server that chunks source code, generates embeddings via Ollama, and stores them in Qdrant for natural-language code search.
    10
  • F
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    Provides a Google search tool via the Serper API, returning structured results and a summary answer for LLMs like Claude.
    1
  • F
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    Enables AI agents to semantically search and navigate code repositories using natural language, with support for multiple repos, incremental indexing, and no local install needed.
  • F
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    A minimalist indexing tool that provides AI agents with semantic search and structural AST parsing for deep codebase understanding. It enables autonomous agents to navigate large codebases predictably using vector embeddings and native language server capabilities like definition and reference tracking.
  • A
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    Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.
    6
    16
    MIT
  • A
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    A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.
    MIT
  • A
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    Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.
    MIT
  • A
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    Enables semantic code search across multiple repositories using AST-aware chunking and relationship tracking. Supports local LLM embeddings, real-time indexing, and cross-codebase dependency analysis through vector and graph databases.
    3
    MIT
  • A
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    Enables AI assistants to semantically search and understand code repositories using PostgreSQL with pgvector embeddings. Provides repository indexing, natural language code search, and development task management with git integration.
    MIT
  • A
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    Enables semantic search across your codebase using Google's Gemini embeddings and Qdrant Cloud vector storage. Supports 15+ programming languages with smart code chunking and real-time file change monitoring.
    125
    19
    MIT